Publication: An alternative semiparametric model for spatial panel data
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2020-12-01
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Springer
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Abstract
We propose a semiparametric P-Spline model to deal with spatial panel data. This model includes a non-parametric spatio-temporal trend, a spatial lag of the dependent variable, and a time series autoregressive noise. Specifically, we consider a spatio-temporal ANOVA model, disaggregating the trend into spatial and temporal main effects, as well as second- and third-order interactions between them. Algorithms based on spatial anisotropic penalties are used to estimate all the parameters in a closed form without the need for multidimensional optimization. Monte Carlo simulations and an empirical analysis of regional unemployment in Italy show that our model represents a valid alternative to parametric methods aimed at disentangling strong and weak cross-sectional dependence when both spatial and temporal heterogeneity are smoothly distributed.
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Spatial panel, Spatio-temporal trend, Mixed models, P-splines, PS-ANOVA
Bibliographic citation
Mínguez, R., Basile, R., & Durbán, M. (2020). An alternative semiparametric model for spatial panel data. Statistical Methods & Applications, 29 (4), pp. 669-708.